pyocd_read_symbol

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden. It discloses key behaviors: combination of ELF lookup and memory read, return of address/raw bytes/interpreted value, and hex dump for complex types. It does not mention error conditions, permissions, or side effects, but the read-only nature and core behavior are well explained. A minor gap in error handling or performance impact prevents a 5.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description consists of three concise sentences that front-load the core purpose and then provide essential details. Every sentence adds value: first sentence states action and resource, second explains the composite nature, third specifies return types. No unnecessary words or repetition.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has an output schema (context: true), the description does not need to detail return values but still does so helpfully. The description is complete for a composite read tool: it explains what it does, how it works, what parameters are used (delegated to schema), and what the output looks like. No gaps are apparent for an agent to invoke it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Both parameters ('name', 'size') have full descriptions in the input schema, providing examples and default behavior. The tool description does not add additional semantic meaning beyond what the schema already conveys. Per guidelines, with 100% schema coverage, a baseline of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'read' and the resource 'global variable's value by symbol name'. It distinguishes from sibling tools like pyocd_memory_read (raw memory read by address) and pyocd_elf_lookup (symbol address lookup) by explaining it combines both operations. The return types (address, raw bytes, interpreted value, hex dump for structs/arrays) are specified, leaving no ambiguity about its functionality.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context: use this tool when you have a symbol name and want to read its value. However, it does not explicitly state when not to use it or mention alternative tools (e.g., pyocd_memory_read for addresses, pyocd_elf_lookup for just the address). While the context is clear, the lack of exclusionary guidance prevents a perfect score.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.